{"id":43895471,"url":"https://github.com/friendsofstrandseq/ashleys-qc","last_synced_at":"2026-02-06T17:20:14.838Z","repository":{"id":52207482,"uuid":"296090436","full_name":"friendsofstrandseq/ashleys-qc","owner":"friendsofstrandseq","description":"Automated Selection of High quality Libraries for the Extensive analYsis of Strandseq data (ASHLEYS)","archived":false,"fork":false,"pushed_at":"2022-10-20T15:33:13.000Z","size":5686,"stargazers_count":1,"open_issues_count":1,"forks_count":1,"subscribers_count":4,"default_branch":"master","last_synced_at":"2023-03-09T22:11:28.452Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/friendsofstrandseq.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-09-16T16:36:42.000Z","updated_at":"2021-06-14T20:15:38.000Z","dependencies_parsed_at":"2023-01-20T06:01:05.649Z","dependency_job_id":null,"html_url":"https://github.com/friendsofstrandseq/ashleys-qc","commit_stats":null,"previous_names":[],"tags_count":null,"template":null,"template_full_name":null,"purl":"pkg:github/friendsofstrandseq/ashleys-qc","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/friendsofstrandseq%2Fashleys-qc","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/friendsofstrandseq%2Fashleys-qc/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/friendsofstrandseq%2Fashleys-qc/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/friendsofstrandseq%2Fashleys-qc/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/friendsofstrandseq","download_url":"https://codeload.github.com/friendsofstrandseq/ashleys-qc/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/friendsofstrandseq%2Fashleys-qc/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29169498,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-06T16:33:35.550Z","status":"ssl_error","status_checked_at":"2026-02-06T16:33:30.716Z","response_time":59,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2026-02-06T17:20:14.215Z","updated_at":"2026-02-06T17:20:14.817Z","avatar_url":"https://github.com/friendsofstrandseq.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ashleys-qc\nAutomated Selection of High quality Libraries for the Extensive analYsis of Strandseq data (ASHLEYS)\n\nASHLEYS is developed on Linux environments using Python3.7.\nFor a full working example on how to use ASHLEYS, please take a look at the [processing pipeline](https://github.com/friendsofstrandseq/ashleys-qc-pipeline).\nPlease note that the preprocessing steps in this pipeline, e.g. short-read alignment and read duplicate marking, are always\nrequired to prepare suitable input files for ASHLEYS; the pipeline (code) itself, however, is just an example implementation, and not\n*per se* part of ASHLEYS.\n\n## Setup\nClone the repository via\n``` python\ngit clone https://github.com/friendsofstrandseq/ashleys-qc.git ashleys-qc\ncd ashleys-qc\n```\nThen create and activate the conda environment:\n``` python\nconda env create -f environment/ashleys_env.yml\nconda activate ashleys\n```\nFor final setup, run\n ``` python\npython setup.py install\n```\nNow you should be able to see all possible modules with\n``` python\n./bin/ashleys.py --help\n```\n\n## Build status\n\nDevelop branch:\n\n[![Build Status](https://travis-ci.org/friendsofstrandseq/ashleys-qc.svg?branch=develop)](https://travis-ci.org/friendsofstrandseq/ashleys-qc)\n\nMaster branch:\n\n[![Build Status](https://travis-ci.org/friendsofstrandseq/ashleys-qc.svg?branch=master)](https://travis-ci.org/friendsofstrandseq/ashleys-qc)\n\n## Feature Generation\nCompute features for one or more BAM files for a given window size. For a detailed explanation\nof what features are computed, please refer to the [feature documentation](docs/Features.md).\n\nExample usage generating all necessary features for using the pretrained models for all\n.bam files in the specified directory:\n``` python\n./bin/ashleys.py -j 23 features -f [folder_with_bamfiles] -w 5000000 2000000 1000000 \\\n 800000 600000 400000 200000 -o [feature_table.tsv]\n```\n\n## Model Training\nTrain a new classification model based on an annotation file specifying class 1 cells.\nThe model is trained with support vector classification based on grid search on hyperparamters. \u003cbr\u003e\nExample usage:\n``` python\n./bin/ashleys.py train -p [feature_table.tsv] -a [annotation.txt] -o [output.tsv]\n```\n\n## Prediction\nPredict the class probabilities for new cells based on pre-trained models or based on customized models. \u003cbr\u003e\nThe default model trained with support vector classification should identify low-quality cells of new data with high confidence. \nFor detailed information about the generated files, please refer to the [output interpretation](docs/Output.md). \n\nExample usage for prediction based on this pretrained model:\n``` python\n./bin/ashleys.py predict -p [feature_table.tsv] -o [output_folder] -m models/svc_default.pkl\n```\nWhen using the pretrained models, it is necessary to have `scikit-learn v.0.23.2` installed, as the models were generated with this version. \nFor customized models also a newer version of `scikit-learn` can be used.\n\n## Plotting\nPlot the distribution of prediction probabilities. \u003cbr\u003e\nExample usage:\n``` python\n./bin/ashleys.py plot -p [output_folder]/prediction.tsv -o [output_plot]\n```\n\n## Test Data\nExample of test data prediction which directly compares the predicted class to the true annotation:\n``` python\n./bin/ashleys.py predict -p data/test_features.tsv -o prediction.tsv \\\n-m models/svc_default.pkl -a data/test_annotation.txt\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffriendsofstrandseq%2Fashleys-qc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffriendsofstrandseq%2Fashleys-qc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffriendsofstrandseq%2Fashleys-qc/lists"}